MonoScene is a CVPR 2022 research project that reconstructs complete 3D semantic scenes from a single monocular image. It uses a deep learning approach with a frustum fusion strategy and global context aggregation to predict voxel-based semantic occupancy in 3D space. The framework is implemented in PyTorch and trained on datasets like SemanticKITTI, KITTI-360, and NYUv2.